Suppr超能文献

公共卫生领域的互操作性和数据连通性问题。

The Issues of Interoperability and Data Connectedness for Public Health.

机构信息

RAND Corporation, Arlington, Virginia, USA.

RAND Corporation, Santa Monica, California, USA.

出版信息

Big Data. 2022 Sep;10(S1):S19-S24. doi: 10.1089/big.2022.0207.

Abstract

An unprecedented amount of data is being collected across a diversity of sectors, which, if harnessed, could transform public health decision-making. Yet significant challenges stand in the way of such a vision, including the need to establish standards of data sharing and interoperability, the need for innovation in both methodological approaches and workforce models, and the need for data stewardship and governance models to ensure the protection and integrity of the public health data system. As with other articles in this supplement, this article builds from a literature review, environmental scan, and deliberations from the National Commission to Transform Public Health Data Systems. The article summarizes some of the challenges around data sharing and reuse and identifies where the technology and data sectors can contribute to fill current gaps to promote interoperability and data stewardship.

摘要

正在从各个领域收集前所未有的大量数据,如果加以利用,可能会改变公共卫生决策。然而,要实现这一愿景,仍然存在重大挑战,包括需要建立数据共享和互操作性标准、在方法和劳动力模式方面进行创新,以及需要数据治理和管理模式来确保公共卫生数据系统的保护和完整性。与该增刊中的其他文章一样,本文基于文献综述、环境扫描以及国家公共卫生数据系统转型委员会的审议。本文总结了数据共享和重用方面的一些挑战,并确定了技术和数据部门可以在哪些方面做出贡献,以弥合当前差距,促进互操作性和数据治理。

相似文献

引用本文的文献

5
Applying Machine Learning Techniques to Implementation Science.将机器学习技术应用于实施科学。
Online J Public Health Inform. 2024 Apr 22;16:e50201. doi: 10.2196/50201.

本文引用的文献

3
Shadow health records meet new data privacy laws.电子健康档案符合新的数据隐私法。
Science. 2019 Feb 1;363(6426):448-450. doi: 10.1126/science.aav5133.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验